1. Anuncie Aqui ! Entre em contato fdantas@4each.com.br

[Python] [[Solved]] Face recognition test failing with correct image [duplicate]

Discussão em 'Python' iniciado por Stack, Setembro 13, 2024.

  1. Stack

    Stack Membro Participativo

    I'm beginning to explore face recognition but even my simple "hello world" is blowing up on my face.

    Here's the code:

    import face_recognition
    from PIL import Image
    import numpy as np
    import base64
    from io import BytesIO

    def test_face_recognition(image_path):
    # Open the image and ensure it's in RGB format
    img = Image.open(image_path).convert('RGB')

    # Convert image to numpy array
    img_np = np.array(img)

    # Check face detection
    face_locations = face_recognition.face_locations(img_np)
    print(f"Faces detected: {len(face_locations)}")

    if len(face_locations) > 0:
    face_encodings = face_recognition.face_encodings(img_np, known_face_locations=face_locations)
    print(f"Encodings found: {len(face_encodings)}")
    else:
    print("No faces detected.")

    # Replace with the path to a local image file
    test_face_recognition("test_image.jpg")


    The test_image.jpg can be any JPEG file with a face on it.

    When run, the code above explodes with the following error message:

    Traceback (most recent call last):
    File "C:\Users\User\source\repos\ballot-box\flask\test_face_recognition.py", line 25, in <module>
    test_face_recognition("test_image.jpg")
    File "C:\Users\User\source\repos\ballot-box\flask\test_face_recognition.py", line 15, in test_face_recognition
    face_locations = face_recognition.face_locations(img_np)
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "C:\Users\User\source\repos\ballot-box\flask\venv\Lib\site-packages\face_recognition\api.py", line 121, in face_locations
    return [_trim_css_to_bounds(_rect_to_css(face), img.shape) for face in _raw_face_locations(img, number_of_times_to_upsample, model)]
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "C:\Users\User\source\repos\ballot-box\flask\venv\Lib\site-packages\face_recognition\api.py", line 105, in _raw_face_locations
    return face_detector(img, number_of_times_to_upsample)
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    RuntimeError: Unsupported image type, must be 8bit gray or RGB image.


    According to the error message, the image is in an invalid format but, before passing the face recognition function, I do convert to the appropriated format: img = Image.open(image_path).convert('RGB')

    Edited:

    I changed from img_np to img to no avail. Now it explodes with the following error:

    Traceback (most recent call last):
    File "C:\Users\PauloSantos\source\repos\ballot-box\flask\test_face.py", line 25, in <module>
    test_face_recognition("test_image.jpg")
    File "C:\Users\PauloSantos\source\repos\ballot-box\flask\test_face.py", line 15, in test_face_recognition
    face_locations = face_recognition.face_locations(img)
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "C:\Users\PauloSantos\source\repos\ballot-box\flask\venv\Lib\site-packages\face_recognition\api.py", line 121, in face_locations
    return [_trim_css_to_bounds(_rect_to_css(face), img.shape) for face in _raw_face_locations(img, number_of_times_to_upsample, model)]
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "C:\Users\PauloSantos\source\repos\ballot-box\flask\venv\Lib\site-packages\face_recognition\api.py", line 105, in _raw_face_locations
    return face_detector(img, number_of_times_to_upsample)
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    TypeError: __call__(): incompatible function arguments. The following argument types are supported:
    1. (self: _dlib_pybind11.fhog_object_detector, image: numpy.ndarray, upsample_num_times: int = 0) -> _dlib_pybind11.rectangles

    Invoked with: <_dlib_pybind11.fhog_object_detector object at 0x000001A8DB8E0370>, <PIL.Image.Image image mode=RGB size=1280x720 at 0x1A8FBD47110>, 1


    Solved

    The problem is the numpy version 2.0. According to this answer the problem occurs due to a breaking change on numpy. Reverting to numpy 1.26.4 solved the problem.

    Continue reading...

Compartilhe esta Página